# 管道搭建示例
## 基于天池 大航杯"智造扬中”电力AI (失败解决方案)
详细请见[博文](http://blog.zhanglun.me/2017/06/13/%E5%A4%A7%E8%88%AA%E6%9D%AF%E2%80%9C%E6%99%BA%E9%80%A0%E6%89%AC%E4%B8%AD%E2%80%9D%E7%94%B5%E5%8A%9BAI%E5%A4%A7%E8%B5%9B%E5%8F%82%E8%B5%9B%E7%BB%8F%E9%AA%8C/)
#### 文件夹介绍
code --主要代码文件
dataset --数据文件
项目依赖:
python3
numpy
pandas
scipy
sklearn
mlxtend
数据挖掘管道搭建示例 基于大航杯“智造扬中”电力AI大赛.zip
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2024-03-07
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数据挖掘管道搭建示例 基于大航杯“智造扬中”电力AI大赛.zip （31个子文件） 
electricAI-master dataset 
yangzhong.csv 30KB train.csv 15.79MB holiday.csv 8KB README.md 443B code visualize.ipynb 65KB combine_fetures.ipynb 234KB clean_data.py 2KB trick_extract.py 3KB extract_fetures.ipynb 41KB clean_data.ipynb 7KB split_samples.ipynb 12KB weather_crawl.py 1KB extract_fetures.py 13KB run.ipynb 4KB trick_extract.ipynb 67KB predict_result.ipynb 4KB
result.txt 46KB rules.ipynb 3KB .ipynb_checkpoints rules-checkpoint.ipynb 3KB split_samples-checkpoint.ipynb 12KB visualize-checkpoint.ipynb 54KB trick_extract-checkpoint.ipynb 67KB run-checkpoint.ipynb 4KB holiday_crawl-checkpoint.ipynb 4KB combine_fetures-checkpoint.ipynb 234KB predict_result-checkpoint.ipynb 4KB train_model-checkpoint.ipynb 15KB extract_fetures-checkpoint.ipynb 41KB clean_data-checkpoint.ipynb 7KB train_model.ipynb 15KB holiday_crawl.ipynb 4KB资源评论
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